Many activities that were previously performed in quiet office or home environments are being performed today in acoustically variable situations like a car, a street, or a cafe. For example, a person may desire to communicate with another person using a voice communication channel. The channel may be provided, for example, by a mobile wireless handset or headset, a walkie-talkie, a two-way radio, a car-kit, or another communications device. Consequently, a substantial amount of voice communication is taking place using mobile devices (e.g., smartphones, handsets, and/or headsets) in environments where users are surrounded by other people, with the kind of noise content that is typically encountered where people tend to gather. Such noise tends to distract or annoy a user at the far end of a telephone conversation. Moreover, many standard automated business transactions (e.g., account balance or stock quote checks) employ voice recognition based data inquiry, and the accuracy of these systems may be significantly impeded by interfering noise.
For applications in which communication occurs in noisy environments, it may be desirable to separate a desired speech signal from background noise. Noise may be defined as the combination of all signals interfering with or otherwise degrading the desired signal. Background noise may include numerous noise signals generated within the acoustic environment, such as background conversations of other people, as well as reflections and reverberation generated from the desired signal and/or any of the other signals. Unless the desired speech signal is separated from the background noise, it may be difficult to make reliable and efficient use of it. In one particular example, a speech signal is generated in a noisy environment, and speech processing methods are used to separate the speech signal from the environmental noise.
Noise encountered in a mobile environment may include a variety of different components, such as competing talkers, music, babble, street noise, and/or airport noise. As the signature of such noise is typically nonstationary and close to the user's own frequency signature, the noise may be hard to suppress using traditional single microphone or fixed beamforming type methods. Single microphone noise reduction techniques typically suppress only stationary noises and often introduce significant degradation of the desired speech while providing noise suppression. However, multiple-microphone-based advanced signal processing techniques are typically capable of providing superior voice quality with substantial noise reduction and may be desirable for supporting the use of mobile devices for voice communications in noisy environments.
Voice communication using headsets can be affected by the presence of environmental noise at the near-end. The noise can reduce the signal-to-noise ratio (SNR) of the signal being transmitted to the far-end, as well as the signal being received from the far-end, detracting from intelligibility and reducing network capacity and terminal battery life.
Active noise cancellation (ANC, also called active noise reduction) is a technology that actively reduces ambient acoustic noise by generating a waveform that is an inverse form of the noise wave (e.g., having the same level and an inverted phase), also called an “antiphase” or “anti-noise” waveform. An ANC system generally uses one or more microphones to pick up an external noise reference signal, generates an anti-noise waveform from the noise reference signal, and reproduces the anti-noise waveform through one or more loudspeakers. This anti-noise waveform interferes destructively with the original noise wave to reduce the level of the noise that reaches the ear of the user.
Active noise cancellation techniques may be applied to sound reproduction devices, such as headphones, and personal communications devices, such as cellular telephones, to reduce acoustic noise from the surrounding environment. In such applications, the use of an ANC technique may reduce the level of background noise that reaches the ear (e.g., by up to twenty decibels) while delivering useful sound signals, such as music and far-end voices.